| 1. |
- Brauko, Kalina M., et al.
(författare)
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Marine Heatwaves, Sewage and Eutrophication Combine to Trigger Deoxygenation and Biodiversity Loss: A SW Atlantic Case Study
- 2020
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Ingår i: Frontiers in Marine Science. - : Frontiers Media SA. - 2296-7745. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- Marine heatwaves (MHWs) are a major concern worldwide due to their increasing impacts in recent years, and these extreme events may trigger deoxygenation of coastal waters affected by sewage and eutrophication. Here we investigate the combined effects of MHWs and nutrient enrichment on the water quality and biodiversity of the Bay of Santa Catarina Island (Brazil). We used historical (1994–2020) sea surface temperature data from satellites and in situ physical, chemical and biological parameters to assess temporal trends. Oxygen levels have been decreasing whilst phosphorus levels have been increasing in the bay. During the austral summer of 2020 a regional sea surface heatwave was detected by satellite, lasting for 9 days and coinciding with our research cruise. During this period, seawater temperatures reached 29.8°C and anoxia was detected for the first time in the bay. A decrease in macrobenthic and phytoplankton community richness correlated with decreases in oxygen both through time and towards more urbanized areas. Overall, poor wastewater treatment is a key stressor that combined with MHWs to degrade coastal waters. Mitigation strategies are needed to minimize the impact of MHWs, including improved sewage treatment, restoration and conservation of wetlands and the use of nature-based technologies to promote coastal ecosystem recovery.
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| 2. |
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| 3. |
- Tavares, Julia, et al.
(författare)
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Basin-wide variation in tree hydraulic safety margins predicts the carbon balance of Amazon forests
- 2023
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Ingår i: Nature. - : Springer Nature. - 0028-0836 .- 1476-4687. ; 617:7959, s. 111-117
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Tidskriftsartikel (refereegranskat)abstract
- Tropical forests face increasing climate risk(1,2), yet our ability to predict their response to climate change is limited by poor understanding of their resistance to water stress. Although xylem embolism resistance thresholds (for example, ?(50)) and hydraulic safety margins (for example, HSM50) are important predictors of drought-induced mortality risk(3-5), little is known about how these vary across Earth's largest tropical forest. Here, we present a pan-Amazon, fully standardized hydraulic traits dataset and use it to assess regional variation in drought sensitivity and hydraulic trait ability to predict species distributions and long-term forest biomass accumulation. Parameters ?(50) and HSM50 vary markedly across the Amazon and are related to average long-term rainfall characteristics. Both ?(50) and HSM50 influence the biogeographical distribution of Amazon tree species. However, HSM50 was the only significant predictor of observed decadal-scale changes in forest biomass. Old-growth forests with wide HSM50 are gaining more biomass than are low HSM(50 )forests. We propose that this may be associated with a growth-mortality trade-off whereby trees in forests consisting of fast-growing species take greater hydraulic risks and face greater mortality risk. Moreover, in regions of more pronounced climatic change, we find evidence that forests are losing biomass, suggesting that species in these regions may be operating beyond their hydraulic limits. Continued climate change is likely to further reduce HSM50 in the Amazon(6,7), with strong implications for the Amazon carbon sink.
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| 4. |
- Bustin, Stephen A., et al.
(författare)
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The need for transparency and good practices in the qPCR literature
- 2013
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Ingår i: Nature Methods. - : Springer Science and Business Media LLC. - 1548-7091 .- 1548-7105. ; 10:11, s. 1063-1067
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Two surveys of over 1,700 publications whose authors use quantitative real-time PCR (qPCR) reveal a lack of transparent and comprehensive reporting of essential technical information. Reporting standards are significantly improved in publications that cite the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines, although such publications are still vastly outnumbered by those that do not.
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| 5. |
- de Melo Barros Junior, Paulo Roberto, et al.
(författare)
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Multi-fractal detrended cross-correlation heatmaps for time series analysis
- 2022
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Ingår i: Scientific Reports. - : NATURE PORTFOLIO. - 2045-2322. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- Complex systems in biology, climatology, medicine, and economy hold emergent properties such as non-linearity, adaptation, and self-organization. These emergent attributes can derive from large-scale relationships, connections, and interactive behavior despite not being apparent from their isolated components. It is possible to better comprehend complex systems by analyzing cross-correlations between time series. However, the accumulation of non-linear processes induces multiscale structures, therefore, a spectrum of power-law exponents (the fractal dimension) and distinct cyclical patterns. We propose the Multifractal detrended cross-correlation heatmaps (MF-DCCHM) based on the DCCA cross-correlation coefficients with sliding boxes, a systematic approach capable of mapping the relationships between fluctuations of signals on different scales and regimes. The MF-DCCHM uses the integrated series of magnitudes, sliding boxes with sizes of up to 5% of the entire series, and an average of DCCA coefficients on top of the heatmaps for the local analysis. The heatmaps have shown the same cyclical frequencies from the spectral analysis across different multifractal regimes. Our dataset is composed of sales and inventory from the Brazilian automotive sector and macroeconomic descriptors, namely the Gross Domestic Product (GDP) per capita, Nominal Exchange Rate (NER), and the Nominal Interest Rate (NIR) from the Central Bank of Brazil. Our results indicate cross-correlated patterns that can be directly compared with the power-law spectra for multiple regimes. We have also identified cyclical patterns of high intensities that coincide with the Brazilian presidential elections. The MF-DCCHM uncovers non-explicit cyclic patterns, quantifies the relations of two non-stationary signals (noise effect removed), and has outstanding potential for mapping cross-regime patterns in multiple domains.
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| 6. |
- Kehoe, Laura, et al.
(författare)
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Make EU trade with Brazil sustainable
- 2019
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 364:6438, s. 341-
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 7. |
- Oliveira, Helena Rodrigues, et al.
(författare)
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Biogas potential of biowaste: A case study in the state of Rio de Janeiro, Brazil
- 2024
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Ingår i: Renewable energy. - : PERGAMON-ELSEVIER SCIENCE LTD. - 0960-1481 .- 1879-0682. ; 221
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Tidskriftsartikel (refereegranskat)abstract
- Anaerobic digestion has been widely applied for waste treatment, renewable energy generation , biofertilizer production. The biogas potential in Brazil is sizable, but the state of Rio de Janeiro is largely dependent on fossil fuels , there is a lack of biogas potential assessments in the state. Thus, this study evaluated biomethane, electricity and biofertilizer potentials in the region. Three different scenarios of biomass supply were considered for four major biowaste streams: sewage sludge; cattle manure; sugarcane processing waste; and food waste. Biomethane generation from the assessed sources could reach 0.6-1.3 billion Nm(3) year(-1), corresponding to 1,768-3,961 GWh year(-1) of electricity , 1.6-3.3 million Mg year- 1 of biofertilizer. Cattle manure was responsible for 73-84% of the projected biomethane production, presenting an opportunity to reduce the sig-nificant emissions from livestock farming. The estimated biofertilizer production could meet the demands of the state , the produced electricity could offset up to 10% of the demand. The gas grid could facilitate the dis-tribution of upgraded biomethane, and 10-22% of the natural gas demand could be met. The findings of this work highlight the high potential for biogas generation in Rio de Janeiro, which is up to seven times larger than the current production.
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| 8. |
- Serravalle Reis Rodrigues, Vitor Hugo, et al.
(författare)
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Wavelet Gated Multiformer for Groundwater Time Series Forecasting
- 2023
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Ingår i: Scientific Reports. - Nature Publishing Group : Research Square Platform LLC.
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Developing accurate models for groundwater control is paramount for planning and managing life-sustaining resources (water) from aquifer reservoirs. Significant progress has been made toward designing and employing deep-forecasting models to tackle the challenge of multivariate time-series forecasting. However, most models were initially taught only to optimize natural language processing and computer vision tasks. We propose the Wavelet Gated Multiformer, which combines the strength of a vanilla Transformer with the Wavelet Crossformer that employs inner wavelet cross-correlation blocks. The self-attention mechanism (Transformer) computes the relationship between inner time-series points, while the cross-correlation finds trending periodicity patterns. The multi-headed encoder is channeled through a mixing gate (linear combination) of sub-encoders (Transformer and Wavelet Crossformer) that output trending signatures to the decoder. This process can improve the model's predictive capabilities. We have also used the Multifractal Detrended Cross-Correlation Heatmaps (MF-DCCHM) to extract cyclical trends from pairs of stations across multifractal regimes by denoising the pair of signals with Daubechies wavelets. Our dataset was obtained from a network of eight wells for groundwater monitoring in Brazilian aquifers, six rainfall stations, eleven river flow stations, and three weather stations with atmospheric pressure, temperature, and humidity sensors.
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| 9. |
- Serravalle Reis Rodrigues, Vitor Hugo, et al.
(författare)
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Wavelet gated multiformer for groundwater time series forecasting
- 2023
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Ingår i: Scientific Reports. - : NATURE PORTFOLIO. - 2045-2322. ; 13:1
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Developing accurate models for groundwater control is paramount for planning and managing life-sustaining resources (water) from aquifer reservoirs. Significant progress has been made toward designing and employing deep-forecasting models to tackle the challenge of multivariate time-series forecasting. However, most models were initially taught only to optimize natural language processing and computer vision tasks. We propose the Wavelet Gated Multiformer, which combines the strength of a vanilla Transformer with the Wavelet Crossformer that employs inner wavelet cross-correlation blocks. The self-attention mechanism (Transformer) computes the relationship between inner time-series points, while the cross-correlation finds trending periodicity patterns. The multi-headed encoder is channeled through a mixing gate (linear combination) of sub-encoders (Transformer and Wavelet Crossformer) that output trending signatures to the decoder. This process improved the model’s predictive capabilities, reducing Mean Absolute Error by 31.26 % compared to the second-best performing transformer-like models evaluated. We have also used the Multifractal Detrended Cross-Correlation Heatmaps (MF-DCCHM) to extract cyclical trends from pairs of stations across multifractal regimes by denoising the pair of signals with Daubechies wavelets. Our dataset was obtained from a network of eight wells for groundwater monitoring in Brazilian aquifers, six rainfall stations, eleven river flow stations, and three weather stations with atmospheric pressure, temperature, and humidity sensors.
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| 10. |
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- 2019
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Tidskriftsartikel (refereegranskat)
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